Szachy w erze cyfrowej
Wpływ mediów społecznościowych i internetu na
popularyzacje szachów,
jak te dane wykorzystać i jak wprowadzić
nowość w szachach.
Rafal Bazan
2024-05-21
Początkowe ustawienia
Css
.my_button {
background-color: #caa8b1;
color: #3c2a34;
padding: 10px;
font-size: 14px;
border: none;
cursor: pointer;
width: 70px;
}
h1, h2, h3, h4, h5, h6 {
text-align: center;
color: #e0cdd6;
}
body {
background-color: #3c2a34;
}
table {
margin:1em auto;
color: #e0cdd6;
}Definiowanie ścieżek
project_path = "D:/moje/projekty/chess-in-the-digital-age"
setwd(paste(project_path,"/presentation", sep = ""))
Dataset_path = paste(project_path,"/Dataset", sep = "")
selected_date = "2024-04"
knitr::opts_chunk$set(root= paste(project_path,"/presentation", sep = ""))Definiowanie paczek
library(pander)
panderOptions('digits',7)
library(knitr)
library(rvest)
library(stringi)
library(dplyr)
library(scales)
library(ggplot2)
library(png)
library("patchwork")
library(forcats)
img <- readPNG("../pictures/queens_gambit.png", native = TRUE)
img2 = readPNG("../pictures/candidates_tournament.png", native = TRUE)
img3 = readPNG("../pictures/covid.png", native = TRUE)
img4 = readPNG("../pictures/opening_icon.png", native = TRUE)Wybór tablicy do scrapowania
url = "https://database.lichess.org"
path= "/html/body/div/div[2]/div/section[1]/table"
wezel = html_node(read_html(url), xpath=path)Java-script dla przycisku
const div_my_init = document.getElementById("my_init");
div_init.style.display = 'none';
var button_my_init = document.getElementById("button_my_init");
function hideMy_init() {
if (div_my_init.style.display === 'none') {
div_my_init.style.display = 'block';
button_my_init.innerHTML = "Ukryj";
} else {
div_my_init.style.display = 'none';
button_my_init.innerHTML = "Pokaż";
}
}Czy szachy są coraz popularniejsze?
Scrapowanie danych z lichess
# wybor tabeli z iloscia zagranych partii wedlug miesiaca
games_count_html = html_table(wezel)[[3]]
my_games_count <- data.frame(count=as.numeric(stri_replace_all(games_count_html,"",regex = "\\,"))[-length(games_count_html)])
# wybor lat do analizy na podstawie linkow .zst.torrent
hyperlinks = html_nodes(wezel, "a")
my_href = html_attr(hyperlinks, "href")
links = data.frame(links = paste(url,my_href,sep="/"))
init_links_for_download = links[seq(2,nrow(links), by=2), 1]
# wyodrebnianie lat z linkow
my_year_from_imported_links = data.frame(year=data.frame(stri_match_all(data.frame(init_links_for_download),
regex = "rated_\\s*(.*?)\\s*[-]"))[,2])
Data_games_count = cbind(my_year_from_imported_links,my_games_count)
# szukanie indeksow rozpoczynajacych nowy rok w zbiorze
first_index_of_years=c()
for(i in unique(my_year_from_imported_links)[,]){
first_index_of_years = append(first_index_of_years,which(rev(Data_games_count$year)==i)[1])
}Wizualizacja
my_plot = ggplot(Data_games_count, aes(x = rev(1:nrow(my_games_count)), y = count)) +
# typ wykresu
geom_bar(stat = "identity",aes(fill = year)) +
# opis
labs(x = "Years", y = "Number of chess games", title = "Number of chess games played on the lichess website") +
# legenda
scale_fill_manual(name = "Years", values = unique(Data_games_count$year)) +
expand_limits(x = c(0, NA), y = c(0,NA)) +
scale_x_continuous(breaks = c(rev(first_index_of_years)),
labels = c(rev(unique(my_year_from_imported_links)[,]))) +
scale_y_continuous(labels = unit_format(unit = "M", scale = 1e-6)) +
theme(text = element_text(size = 20),
axis.text.x = element_text(angle = 90, hjust = 1))
my_plot
Szukanie powodów znacznego wzrostu popularności szachów w 2020 roku
# strzalka
my_plot + geom_segment(aes(70, 68000000, xend = 86, yend = 62000000),
linewidth=1.2,
arrow = arrow(length = unit(5, "mm"))) +
# zdjecia
inset_element(p = img,
left = 0.02,
bottom = 0.54,
right = 0.42,
top = 0.9) +
inset_element(p = img2,
left = 0.05,
bottom = 0.29,
right = 0.5,
top = 0.52)+
inset_element(p = img3,
left = 0.44,
bottom = 0.69,
right = 0.65,
top = 0.82)
Wnioski:
- Szachy zyskują na popularności, ale czy na pewno dzięki internetowi i cyfryzacji?
Jak wpłynął serial “Gambit królowej” na szachy?
Ciekawostka:
- Gambit królowej w szachach to nazwa debiutu szachowego. Debiut szachowy z kolei to początkowe posunięcia w szachach.
Gambit Królowej
Ile było granych debiutów “Gambit królowej”?
Tworzenie struktury zbioru danych
wyodrębnianie tagów oraz hiperłączy
hyperlinks = html_nodes(wezel, "a")
my_href = html_attr(hyperlinks, "href")
pander(head(bind_rows(lapply(html_attrs(hyperlinks), function(x) data.frame(as.list(x), stringsAsFactors=FALSE)))))| href |
|---|
| standard/lichess_db_standard_rated_2024-05.pgn.zst |
| standard/lichess_db_standard_rated_2024-05.pgn.zst.torrent |
| standard/lichess_db_standard_rated_2024-04.pgn.zst |
| standard/lichess_db_standard_rated_2024-04.pgn.zst.torrent |
| standard/lichess_db_standard_rated_2024-03.pgn.zst |
| standard/lichess_db_standard_rated_2024-03.pgn.zst.torrent |
Łączenie zmiennych w gotowy do pobrania link
links = data.frame(links = paste(url,my_href,sep="/"))
pander(head(links))Wybór wersji pobierania (.zst.torrent) w funkcji ograniczającej scrapowanie względem wybranej daty
choose_max_date_to_scrap = function(date){
# co drugi link to .zst.torrent wiec go wyodrebniam
init_links_for_download = links[seq(2,nrow(links), by=2), 1]
full_date_from_imported_links = data.frame(stri_match_all(data.frame(init_links_for_download),
regex = "rated_\\s*(.*?)\\s*[.]"))[,2]
date_location = which(stri_detect(full_date_from_imported_links, regex = date) == TRUE)
my_links_for_download = init_links_for_download[c(date_location:length(init_links_for_download))]
return(my_links_for_download)
}
links_for_download = choose_max_date_to_scrap(selected_date)
pander(data.frame(prepared_links = head(links_for_download)))Wyodrębianie daty ze scrapowania
full_date_from_imported_links = data.frame(stri_match_all(data.frame(links_for_download),
regex = "rated_\\s*(.*?)\\s*[.]"))[,2]
pander(head(data.frame(full_date_from_imported_links)))| full_date_from_imported_links |
|---|
| 2024-04 |
| 2024-03 |
| 2024-02 |
| 2024-01 |
| 2023-12 |
| 2023-11 |
Wyodrębianie roku, miesięcy, nazw miesięcy ze scrapowania
year_from_imported_links = data.frame(stri_match_all(data.frame(links_for_download),
regex = "rated_\\s*(.*?)\\s*[-]"))[,2]
pander(head(data.frame(year_from_imported_links)))| year_from_imported_links |
|---|
| 2024 |
| 2024 |
| 2024 |
| 2024 |
| 2023 |
| 2023 |
month_from_imported_links = data.frame(stri_match_all(data.frame(links_for_download),
regex = "-\\s*(.*?)\\s*[.]"))[,2]
pander(head(data.frame(month_from_imported_links)))| month_from_imported_links |
|---|
| 04 |
| 03 |
| 02 |
| 01 |
| 12 |
| 11 |
my_month_names = month.abb[as.integer(month_from_imported_links)]
pander(head(data.frame(my_month_names)))| my_month_names |
|---|
| Apr |
| Mar |
| Feb |
| Jan |
| Dec |
| Nov |
Tworzenie struktury plików - lata
my_paths_year <- unique(paste(Dataset_path,"/",year_from_imported_links, sep=""))
pander(data.frame(my_paths_year))| my_paths_year |
|---|
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2023 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2022 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2021 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2020 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2019 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2018 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2017 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2016 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2015 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2014 |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2013 |
create_folders_year = function(){
for(i in 1:length(my_paths_year)){
dir.create(my_paths_year[i])
}
}Tworzenie struktury plików - miesiące
my_paths_month <- paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names, sep="")
pander(head(data.frame(my_paths_month)))| my_paths_month |
|---|
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/04. Apr |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/03. Mar |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/02. Feb |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/01. Jan |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2023/12. Dec |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2023/11. Nov |
create_folders_month = function(){
for(i in 1:length(my_paths_month)){
dir.create(my_paths_month[i])
}
}Definiowanie ścieżek do których będą pobierane pliki i definiowanie ich docelowych nazw
my_paths = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/lichess_db_standard_rated_",full_date_from_imported_links,".pgn.zst.torrent", sep="")
pander(head(data.frame(my_paths)))| my_paths |
|---|
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/04. Apr/lichess_db_standard_rated_2024-04.pgn.zst.torrent |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/03. Mar/lichess_db_standard_rated_2024-03.pgn.zst.torrent |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/02. Feb/lichess_db_standard_rated_2024-02.pgn.zst.torrent |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2024/01. Jan/lichess_db_standard_rated_2024-01.pgn.zst.torrent |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2023/12. Dec/lichess_db_standard_rated_2023-12.pgn.zst.torrent |
| D:/moje/projekty/chess-in-the-digital-age/Dataset/2023/11. Nov/lichess_db_standard_rated_2023-11.pgn.zst.torrent |
downloading = function(){
create_folders_year()
create_folders_month()
for(j in 1:length(my_paths)){
download.file(links_for_download[j], my_paths[j], mode="wb",Sys.sleep(0.2))
}
}Tworzenie struktury plikow i pobieranie w niej zbiorów danych
downloading()Java-script dla przycisku
const my_div1 = document.getElementById("tworzenie-struktury");
my_div1.style.display = 'none';
var button = document.getElementById("my_button");
function myFunction() {
if (my_div1.style.display === 'none') {
my_div1.style.display = 'block';
button.innerHTML = "Ukryj";
} else {
my_div1.style.display = 'none';
button.innerHTML = "Pokaż";
}
}Przygotowywanie zbiorów danych do użycia
Pobieranie informacji o liczbie partii poprzez scrapowanie oraz ograniczenie tego scrapowania względem wybranej daty
choose_max_date_to_scrap_game_count = function(date){
# wybor tabeli do analizy
my_games_count = html_table(wezel)[[3]]
# wybor lat do analizy na podstawie linkow .zst.torrent
init_links_for_download = links[seq(2,nrow(links), by=2), 1]
# wyodrebnianie dat z linkow
full_date_from_imported_links = data.frame(stri_match_all(data.frame(init_links_for_download),
regex = "rated_\\s*(.*?)\\s*[.]"))[,2]
# szukanie indeksow z datami odpowiadajacymi wybranej dacie
date_location = which(stri_detect(full_date_from_imported_links, regex = date) == TRUE)
# wyswietlanie liczb gier dla wybranych dat
games_count = my_games_count[c(date_location:length(init_links_for_download))]
return(games_count)
}
games_count = choose_max_date_to_scrap_game_count(selected_date)
pander(head(data.frame(games_count)))| games_count |
|---|
| 91,383,489 |
| 95,810,349 |
| 91,628,934 |
| 99,001,912 |
| 96,909,211 |
| 92,389,636 |
funkcja do ograniczania danych dla konkretnego zbioru względem miesiąca
preparing_month_dataset = function(date, data_size = 0.001){
# szukanie indeksu wybranej daty
searching_location = which(stri_detect(full_date_from_imported_links, regex = date) == TRUE)
# szukanie liczby meczy dla wybranej daty i ograniczanie jej wzgledem wyszukanych wartosci
decreasing_game_number <- round((as.numeric(stri_replace_all(games_count,"",regex = "\\,"))*18*data_size)[searching_location])
# definiowanie pliku do przerobki na podstawie wybranej daty
pgn_file_to_read = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/lichess_db_standard_rated_",full_date_from_imported_links,".pgn", sep="")[searching_location]
# wczytanie pliku do zdefiniowanej dlugosci
my_pgn <- read.table(pgn_file_to_read,
quote="", sep="\n", stringsAsFactors=FALSE, nrows = decreasing_game_number)
# szukanie ostatnich 22 nazw kolumn
colnms <- sub("\\[(\\w+).+", "\\1", my_pgn[(decreasing_game_number-22):decreasing_game_number,1])
# szukanie indeksow rozpoczynajacych nowe partie
Event_location = which(stri_detect(colnms, regex = "Event") == TRUE)
# usuwanie danych pod wyszukanym indeksie
my_pgn2 = my_pgn[1:(decreasing_game_number-22+Event_location-2),]
# zapis przetworzonego zbioru do pliku
pgn_file_to_write = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/Data_",date,".pgn", sep="")[searching_location]
write.table(my_pgn2,pgn_file_to_write,col.names = FALSE,row.names = FALSE,quote = FALSE)
test_path = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/Data_",date,".pgn", sep="")[searching_location]
# tworzenie pliku dla statusu pracy
file_txt_for_info = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/ograniczono_dane.txt", sep="")[searching_location]
write.table(" ",file_txt_for_info)
testing_last_char <- read.table(test_path,
quote="", sep="\n", stringsAsFactors=FALSE)
return(tail(testing_last_char))
}funkcja do usuwania oryginalnego zbioru danych względem miesiąca
removing_oryginal_dataset = function(date){
# szukanie indeksu wybranej daty
searching_location = which(stri_detect(full_date_from_imported_links, regex = date) == TRUE)
# definiowanie plikow do usuniecia
file_pgn_zst_to_remove = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/lichess_db_standard_rated_",full_date_from_imported_links,".pgn.zst", sep="")[searching_location]
file_pgn_to_remove = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/lichess_db_standard_rated_",full_date_from_imported_links,".pgn", sep="")[searching_location]
# tworzenie pliku dla statusu pracy
file_txt_for_info = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/usunieto_oryginal.txt", sep="")[searching_location]
file.remove(file_pgn_zst_to_remove)
file.remove(file_pgn_to_remove)
write.table(" ",file_txt_for_info)
}Wywoływanie funkcji przygotowującej zbiór z konkretnego miesiąca do późniejszej analizy
preparing_month_dataset("2013-01")
removing_oryginal_dataset("2013-01")Java-script dla przycisku
const my_div2 = document.getElementById("przygotowywanie-zbiorow");
my_div2.style.display = 'none';
var button2 = document.getElementById("my_button2");
function myFunction2() {
if (my_div2.style.display === 'none') {
my_div2.style.display = 'block';
button2.innerHTML = "Ukryj kod";
} else {
my_div2.style.display = 'none';
button2.innerHTML = "Pokaż kod";
}
}Liczenie zagranych debiutów “Gambit królowej” na przestrzeni lat
# komenda szukajaca powtarzalnosc danej kolumny
# zmienne = fct_count(fct_infreq(sub("\\[(\\w+).+", "\\1", pgn[1:nrow(pgn.df),1])))
files_to_read = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/Data_",full_date_from_imported_links,".pgn", sep="")
Percent_games_count=c()
for(i in 1:length(files_to_read)){
pgn <- read.table(files_to_read[i], quote="", sep="\n", stringsAsFactors=FALSE)
pgn.df <- data.frame(matrix(sub("\\[\\w+ \\\"(.+)\\\"\\]", "\\1", pgn[,1]),
byrow=TRUE, ncol=1))
opening_index = which(sub("\\[(\\w+).+", "\\1", pgn[1:nrow(pgn.df),1]) == "Opening")
All_games_count = length(pgn.df[opening_index,])
Queens_Gambit_games_count = length(which(stri_detect(pgn.df[opening_index,], regex = "Queen's Gambit") == TRUE))
Percent_games_count = append(Percent_games_count,(Queens_Gambit_games_count/All_games_count)*100)
}Przewidywania:
- Skoro termin “Gambit królowej” zyskał rozgłos dzięki serialowi, to debiut o tej nazwie powinien występować częściej po 2020 roku procentowo w stosunku do całości.
Wizualizacja
my_Percent_games_count <- data.frame(count=Percent_games_count)
Data_Queens_gambit_games_count = cbind(data.frame(year=year_from_imported_links),my_Percent_games_count)
ggplot(Data_Queens_gambit_games_count, aes(x = rev(1:length(games_count)), y = count)) +
# typ wykresu
geom_bar(stat = "identity",aes(fill = year)) +
# opis
labs(x = "Years", y = "Number of chess games ( % ) ", title = "Number of 'Queen's Gambit' openings played") +
# legenda
scale_fill_manual(name = "Years", values = unique(Data_Queens_gambit_games_count$year)) +
expand_limits(x = c(0, NA), y = c(0,NA)) +
scale_x_continuous(breaks = c(rev(first_index_of_years)),
labels = c(rev(unique(year_from_imported_links)))) +
scale_y_continuous(labels = unit_format(unit = "%", scale = 1)) +
theme(text = element_text(size = 20),
axis.text.x = element_text(angle = 90, hjust = 1)) 
Obserwacje:
- Widać wyraźnie malejący stosunek granych debiutów “Gambit królowej”, po dacie premiery serialu.
Wnioski:
- Serial znacząco wpłynął na osoby, które nie wiedzą co znaczy termin “Gambit królowej”.
Czy serial wpłynął tylko na nowicjuszy szachowych?
Wyszukiwanie Ilości zagranych partii przez nowicjuszy (ranga < 1200)
files_to_read = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/Data_",full_date_from_imported_links,".pgn", sep="")
novice_games_count=c()
for(i in 1:length(files_to_read)){
pgn <- read.table(files_to_read[i], quote="", sep="\n", stringsAsFactors=FALSE)
pgn.df <- data.frame(matrix(sub("\\[\\w+ \\\"(.+)\\\"\\]", "\\1", pgn[,1]),
byrow=TRUE, ncol=1))
elo_index = which(sub("\\[(\\w+).+", "\\1", pgn[1:nrow(pgn.df),1]) == "WhiteElo")
All_games_count = length(pgn.df[elo_index,])
my_novice_games_count = length(which(as.numeric(pgn.df[elo_index,]) < 1200) == TRUE)
novice_games_count = append(novice_games_count,(my_novice_games_count/All_games_count)*100)
}Wizualizacja
my_Percent_novice_games_count <- data.frame(count=Percent_novice_games_count)
Data_novice_games_count = cbind(data.frame(year=year_from_imported_links),my_Percent_novice_games_count)
ggplot(Data_novice_games_count, aes(x = rev(1:length(games_count)), y = count)) +
# typ wykresu
geom_bar(stat = "identity",aes(fill = year)) +
# opis
labs(x = "Years", y = "Number of chess games ( % ) ", title = "Number of novice games (rank < 1200) ") +
# legenda
scale_fill_manual(name = "Years", values = unique(Data_novice_games_count$year)) +
expand_limits(x = c(0, NA), y = c(0,NA)) +
scale_x_continuous(breaks = c(rev(first_index_of_years)),
labels = c(rev(unique(year_from_imported_links)))) +
scale_y_continuous(labels = unit_format(unit = "%", scale = 1)) +
theme(text = element_text(size = 20),
axis.text.x = element_text(angle = 90, hjust = 1)) +
# strzalka
geom_segment(aes(58, 10.68, xend = 95, yend = 10),
linewidth=1.2,
arrow = arrow(length = unit(5, "mm"))) +
# zdjecia
inset_element(p = img,
left = 0.02,
bottom = 0.54,
right = 0.42,
top = 0.9)
Obserwacje:
- Widać znaczny napływ nowicjuszy po dacie premiery serialu
- Po oglądnięciu serialu, osoby nie znające się na szachach, chcą poprostu zagrać w tą gre i nie interesują się debiutami. To powoduje chęć zagrania na stronie lichess jako nowicjusz.
Wyszukiwanie Ilości zagranych partii przez zaawansowanych graczy (ranga > 1800)
files_to_read = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/Data_",full_date_from_imported_links,".pgn", sep="")
pro_games_count=c()
for(i in 1:length(files_to_read)){
pgn <- read.table(files_to_read[i], quote="", sep="\n", stringsAsFactors=FALSE)
pgn.df <- data.frame(matrix(sub("\\[\\w+ \\\"(.+)\\\"\\]", "\\1", pgn[,1]),
byrow=TRUE, ncol=1))
elo_index_v2 = which(sub("\\[(\\w+).+", "\\1", pgn[1:nrow(pgn.df),1]) == "WhiteElo")
All_games_count_v2 = length(pgn.df[elo_index_v2,])
my_pro_games_count = length(which(as.numeric(pgn.df[elo_index_v2,]) > 1800) == TRUE)
pro_games_count = append(pro_games_count,(my_pro_games_count/All_games_count_v2)*100)
}Wizualizacja
my_Percent_pro_games_count <- data.frame(count=Percent_pro_games_count)
Data_pro_games_count = cbind(data.frame(year=year_from_imported_links),my_Percent_pro_games_count)
ggplot(Data_pro_games_count, aes(x = rev(1:length(games_count)), y = count)) +
# typ wykresu
geom_bar(stat = "identity",aes(fill = year)) +
# opis
labs(x = "Years", y = "Number of chess games ( % ) ", title = "Number of pro games (rank > 1800) ") +
# legenda
scale_fill_manual(name = "Years", values = unique(Data_pro_games_count$year)) +
expand_limits(x = c(0, NA), y = c(0,NA)) +
scale_x_continuous(breaks = c(rev(first_index_of_years)),
labels = c(rev(unique(year_from_imported_links)))) +
scale_y_continuous(labels = unit_format(unit = "%", scale = 1)) +
theme(text = element_text(size = 20),
axis.text.x = element_text(angle = 90, hjust = 1)) +
# strzalka
geom_segment(aes(65, 38, xend = 86, yend = 37),
linewidth=1.2,
arrow = arrow(length = unit(5, "mm"))) +
inset_element(p = img3,
left = 0.39,
bottom = 0.84,
right = 0.6,
top = 0.97)
Obserwacje:
- Widać spadek ilości zaawansowanych graczy po 2020 roku w stosunku do całości
Wnioski:
- Serial wpłynął na popularyzacje szachów, głównie zachęcając do gry nowicjuszy.
Dla czego serial nie wpłynął na zaawansowanych graczy?
- Nie zawierał dla nich nic nowego
Czy dodanie do szachów nowości zwiększy popularność wśród zaawansowanych graczy?
Tworzenie nowego debiutu
Statystyki popularności Anny Cramling na twitch
Wyszukiwanie debiutów po sekwencji posunięć, zamiast po nazwie
#files_to_read = paste(Dataset_path,"/",year_from_imported_links,"/",month_from_imported_links,". ",my_month_names,"/Data_",full_date_from_imported_links,".pgn", sep="")
search_by_moves = function(searching_moves){
opening_count=c()
for(i in 1:length(files_to_read)){
pgn <- read.table(files_to_read[i], quote="", sep="\n", stringsAsFactors=FALSE)
moves = which(sub("\\[(\\b+).+", "\\1", pgn[1:nrow(pgn),1]) != "")
All_games_count = length(pgn[moves,])
for(j in 1:length(searching_moves)){
my_regex = paste("(.*?)\\s*",j,". (\\w+).+", sep = "")
moves_to_compare = sub(my_regex, "\\2", pgn[moves,])
moves = moves[which(moves_to_compare == searching_moves[j])]
}
opening_count = append(opening_count,(length(moves)/All_games_count)*100)
}
return(opening_count)
}
search_by_moves(c("e3","d3","Ne2","Nd2","Ng3"))Wizualizacja
my_opening_count <- data.frame(count=opening_count)
Data_opening_count = cbind(data.frame(year=year_from_imported_links),my_opening_count)
ggplot(Data_opening_count, aes(x = rev(1:length(games_count)), y = count)) +
# typ wykresu
geom_bar(stat = "identity",aes(fill = year)) +
# opis
labs(x = "Years", y = "Number of chess games", title = "Number of 'Cow' move sequences played") +
# legenda
scale_fill_manual(name = "Years", values = unique(Data_opening_count$year)) +
expand_limits(x = c(0, NA), y = c(0, 10)) +
scale_x_continuous(breaks = c(rev(first_index_of_years)),
labels = c(rev(unique(year_from_imported_links)))) +
theme(text = element_text(size = 20),
axis.text.x = element_text(angle = 90, hjust = 1)) +
# strzalka
geom_segment(aes(80, 3.2, xend = 123, yend = 2.2),
linewidth=1.2,
arrow = arrow(length = unit(5, "mm"))) +
inset_element(p = img4,
left = 0.42,
bottom = 0.34,
right = 0.75,
top = 0.51)
Obserwacje:
- Widać wzrost popularności streamerki po opublikowaniu nowego debiutu oraz widać wzrost zainteresowania jej stworzoną sekwencją szachową
Wnioski:
- Ciężko wpłynąć na zaawansowanych graczy. Rolą internetu jest to zmienić.
Podsumowanie
- Internet i media społecznościowe znacząco wpływają na popularyzacje szachów. Na graczy